The SNP and Variation Suite (SVS) software currently supports three methods for genomic prediction: Genomic Best Linear Unbiased Predictors (GBLUP), Bayes C and Bayes C-pi. We have discussed these methods extensively in previous blogs and webcast events. Although there are extensive applications for these methods, they are primarily used for trait selection in agricultural genetics. Each method can be used… Read more »
Personal genome sequencing is rapidly changing the landscape of clinical genetics. With this development also comes a new set of challenges. For example, every sequenced exome presents the clinical geneticist with thousands of variants. The job at hand is to find out which one might be responsible for the person’s illness. In order to reduce the search space, clinicians use various methods… Read more »
SVS offers options for performing many different QC functions on genomic data. This blog takes you through some of the most commonly applied filters for various analysis types. Filters for GWAS data vary depending on the type of association tests you are performing. A typical GWAS for a common variant usually requires filters to remove problematic or poorly called variants,… Read more »
Last month, June 2014, we announced a new method that Golden Helix developed–the soon to be available MM-KBAC. MM-KBAC, or Mixed Model Kernel Based Adaptive Clustering combines the KBAC method developed by Lui and Leal (2010) with a random effects matrix to adjust for relationships between samples. The KBAC algorithm takes a binary dependent variable and transformations are used to convert… Read more »
We released GenomeBrowse 2.0 earlier this year, allowing users to review all types of genomic data. Since then, it has received rave reviews from thousands of users around the world. Essentially, it’s the Google Earth app for genomic data. GenomeBrowse allows a user to sift through vast amounts of genomic data, and make it easy to focus on a single part… Read more »
I’m a believer in the signal. Whole genomes and exomes have lots of signal. Man, is it cool to look at a pile-up and see a mutation as clear as day that you arrived at after filtering through hundreds of thousands or even millions of candidates. When these signals sit right in the genomic “sweet spot” of mappable regions with… Read more »
Speaking as somebody with a long history in data analysis, there are few things I find more exciting and tantalizing than new analysis methods that might apply to a problem I am trying to solve or was unable to solve in the past. Whenever I make a breakthrough in one project, I find I want to abandon the current project… Read more »
In the paper Runs of homozygosity reveal highly penetrant recessive loci in schizophrenia, Todd Lencz, Ph.D. introduced a new way of doing association testing using SNP microarray platforms. The method, which he termed “whole genome homozygosity association”, first identifies patterned clusters of SNPs demonstrating extended homozygosity (runs of homozygosity or “ROHs”) and then employs both genome-wide and regionally-specific statistical tests… Read more »
